import { type Pool, type PoolClient, type PoolConfig } from "pg"; import { VectorStore } from "./base.js"; import { Embeddings } from "../embeddings/base.js"; import { Document } from "../document.js"; type Metadata = Record; /** * Interface that defines the arguments required to create a * `PGVectorStore` instance. It includes Postgres connection options, * table name, filter, and verbosity level. */ export interface PGVectorStoreArgs { postgresConnectionOptions: PoolConfig; tableName: string; columns?: { idColumnName?: string; vectorColumnName?: string; contentColumnName?: string; metadataColumnName?: string; }; filter?: Metadata; verbose?: boolean; } /** * Class that provides an interface to a Postgres vector database. It * extends the `VectorStore` base class and implements methods for adding * documents and vectors, performing similarity searches, and ensuring the * existence of a table in the database. */ export declare class PGVectorStore extends VectorStore { FilterType: Metadata; tableName: string; idColumnName: string; vectorColumnName: string; contentColumnName: string; metadataColumnName: string; filter?: Metadata; _verbose?: boolean; pool: Pool; client?: PoolClient; _vectorstoreType(): string; private constructor(); /** * Static method to create a new `PGVectorStore` instance from a * connection. It creates a table if one does not exist, and calls * `connect` to return a new instance of `PGVectorStore`. * * @param embeddings - Embeddings instance. * @param fields - `PGVectorStoreArgs` instance. * @returns A new instance of `PGVectorStore`. */ static initialize(embeddings: Embeddings, config: PGVectorStoreArgs): Promise; protected _initializeClient(): Promise; /** * Method to add documents to the vector store. It converts the documents into * vectors, and adds them to the store. * * @param documents - Array of `Document` instances. * @returns Promise that resolves when the documents have been added. */ addDocuments(documents: Document[]): Promise; /** * Generates the SQL placeholders for a specific row at the provided index. * * @param index - The index of the row for which placeholders need to be generated. * @returns The SQL placeholders for the row values. */ private generatePlaceholderForRowAt; /** * Constructs the SQL query for inserting rows into the specified table. * * @param rows - The rows of data to be inserted, consisting of values and records. * @param chunkIndex - The starting index for generating query placeholders based on chunk positioning. * @returns The complete SQL INSERT INTO query string. */ private buildInsertQuery; /** * Method to add vectors to the vector store. It converts the vectors into * rows and inserts them into the database. * * @param vectors - Array of vectors. * @param documents - Array of `Document` instances. * @returns Promise that resolves when the vectors have been added. */ addVectors(vectors: number[][], documents: Document[]): Promise; /** * Method to perform a similarity search in the vector store. It returns * the `k` most similar documents to the query vector, along with their * similarity scores. * * @param query - Query vector. * @param k - Number of most similar documents to return. * @param filter - Optional filter to apply to the search. * @returns Promise that resolves with an array of tuples, each containing a `Document` and its similarity score. */ similaritySearchVectorWithScore(query: number[], k: number, filter?: this["FilterType"]): Promise<[Document, number][]>; /** * Method to ensure the existence of the table in the database. It creates * the table if it does not already exist. * * @returns Promise that resolves when the table has been ensured. */ ensureTableInDatabase(): Promise; /** * Static method to create a new `PGVectorStore` instance from an * array of texts and their metadata. It converts the texts into * `Document` instances and adds them to the store. * * @param texts - Array of texts. * @param metadatas - Array of metadata objects or a single metadata object. * @param embeddings - Embeddings instance. * @param dbConfig - `PGVectorStoreArgs` instance. * @returns Promise that resolves with a new instance of `PGVectorStore`. */ static fromTexts(texts: string[], metadatas: object[] | object, embeddings: Embeddings, dbConfig: PGVectorStoreArgs): Promise; /** * Static method to create a new `PGVectorStore` instance from an * array of `Document` instances. It adds the documents to the store. * * @param docs - Array of `Document` instances. * @param embeddings - Embeddings instance. * @param dbConfig - `PGVectorStoreArgs` instance. * @returns Promise that resolves with a new instance of `PGVectorStore`. */ static fromDocuments(docs: Document[], embeddings: Embeddings, dbConfig: PGVectorStoreArgs): Promise; /** * Closes all the clients in the pool and terminates the pool. * * @returns Promise that resolves when all clients are closed and the pool is terminated. */ end(): Promise; } export {};